GLM Ch. 18
General Design Classifications for Selection of Difference Statistical Methods
Key Terms
- Each participant in the research is in one and only one condition or group
- Participants receive only one level of the IV
- DV only needs to be measured once
- If power analysis says 20 in each group, then you need 60 total
- Each participant receives or experiences ALL levels of the IV
- If power analysis says 20 in each group, then you need 20 total
- Appeal is in need for fewer participants acting as own controls
- Impacted by carryover effects
- Has at least one between-groups IV and one within-subjects IV
- Has a minimum of two IVs
Understanding Design Types
It’s all about the levels of the IV
Designs are usually described in terms of:
- the general type of design (between groups, within subjects, or mixed)
- the number of independent variables
- the number of levels within each independent variable.
What does this mean?
The researcher will typically state the design:
EX: A single factor design with 3 levels
EX: A 2 x 2 design with repeated measures
EX: A 3 x 3 x 2 factorial design
Single Factor Designs
Note: Factor is another name for IV
Single factor designs only have one IV
EX: The effect of time of class (morning, afternoon, night) on student engagement.
EX: Students’ perceptions of instructor effectiveness over time.
Class Example
Ikeola and Marian are examining campaigns using visual images can influence HPV vaccine behavioral intentions and eventual uptake of the HPV vaccine.
- IV: Visual message (4 levels: threat, efficacy, threat x efficacy, control)
- DV: Behavioral intentions
Between-Groups Factorial Designs
Includes more than one IV
EX: The effect of time of class (morning, afternoon, night) and student sex (male, female) on student engagement.
This is called a 3 x 2 factorial design.
Think Fast!
If you have a 4 x 2 x 3 factorial design…
How many IVs do you have?
What are the levels of each IV?
How many groups would you need for the study?
Class Example
Elizabeth, Madelyn, and Ansley are examining how message sender status on Instagram influences behavioral intention / adoption.
- IV: Status (3 levels: influencer, layperson, control)
- DV: Behavioral intention
This is currently a single-subject design. How would you make it a between-subjects design?
Within-Subjects Factorial Designs
Two or more IVs
Participants experience all conditions
EX: The effect of teaching style (traditional or inquiry based) on student engagement over time (pretest and posttest)
Example
To assess the CIS courses in the School of Information Science, we collect data from all course sections in August, December, January, and April to see if participation in course influences public speaking self-efficacy.
EX: The effect of class time on public speaking self-efficacy over time.
Mixed Designs
“Such a design might have two between-groups independent variables with three and four levels, respectively, and have one within-subjects independent variable with two levels.
It would be described as a 3 × 4 × 2 factorial design with repeated measures on the third factor.”
Basically, if it has a BG component and a WS component, it is a mixed design!
Summing it Up
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If you recognize the design, you can generally determine the type of test needed.
